@inproceedings{gaugaz2012predicting,
  abstract = {The amount of news content on the Web is increasing: Users can access news articles coming from a variety of sources on the Web: from newswires, news agencies, blogs, and at various places, e.g. even within Web search engines result pages. Anyhow, it still is a challenge for current search engines to decide which news events are worth being shown to the user (either for a newsworthy query or in a news portal). In this paper we define the task of predicting the future impact of news events. Being able to predict event impact will, for example, enable a newspaper to decide whether to follow a specific event or not, or a news search engine which stories to display. We define a flexible framework that, given some definition of impact, can predict its future development at the beginning of the event. We evaluate several possible definitions of event impact and experimentally identify the best features for each of them.},
  author = {Gaugaz, Julien and Siehndel, Patrick and Demartini, Gianluca and Iofciu, Tereza and Georgescu, Mihai and Henze, Nicola},
  booktitle = {Proc. of the 34th European Conference on Information Retrieval (ECIR 2012)},
  interhash = {dc898856b5a18bf1cb9307d1bd9b5268},
  intrahash = {f29c05f9a4fc3bb2189a965d95f622f9},
  location = {Barcelona, Spain},
  month = apr,
  title = {Predicting the Future Impact of News Events},
  url = {http://www.l3s.de/web/page25g.do?kcond12g.att1=1833},
  year = 2012
}

@phdthesis{HELL,
  author = {HELLBRÜGGE, B. and TÖLLE, K.-H. and BENNEWITZ, J. and HENZE, C. and PRESUHN, U. and KRIETER, J.},
  interhash = {a7d26419d427dd8d88617063e7081ab6},
  intrahash = {2f96a9c09ac03ccdae2fae0b17ac3ccc},
  title = {Genetic relationship between maternal behaviour in sows and piglet mortality
in Genetic aspects of piglet losses and the maternal behaviour of sows
},
  year = 2007
}

@inproceedings{Abel:2008:RFS:1458082.1458316,
  acmid = {1458316},
  address = {New York, NY, USA},
  author = {Abel, Fabian and Henze, Nicola and Krause, Daniel},
  booktitle = {Proceeding of the 17th ACM conference on Information and knowledge management},
  doi = {http://doi.acm.org/10.1145/1458082.1458316},
  interhash = {5d6db50409eef97339b135ab8f703538},
  intrahash = {f66b82fc919462c25698392c3cf4e6fa},
  isbn = {978-1-59593-991-3},
  location = {Napa Valley, California, USA},
  numpages = {2},
  pages = {1429--1430},
  publisher = {ACM},
  series = {CIKM '08},
  title = {Ranking in folksonomy systems: can context help?},
  url = {http://doi.acm.org/10.1145/1458082.1458316},
  year = 2008
}

@inproceedings{abel_CIKM_2008,
  abstract = {Folksonomy systems have shown to contribute to the quality of Web search ranking strategies. In this paper, we analyze and compare different graph-based ranking algorithms, namely FolkRank, SocialPageRank, and SocialSimRank. We enhance these algorithms by exploiting the context of tag assignmets, and evaluate the results on the GroupMe! dataset. In GroupMe!, users can organize and maintain arbitrary Web resources in self-defined groups. When users annotate resources in GroupMe!, this can be interpreted in context of a certain group. The grouping activity delivers valuable semantic information about resources and their context. We show how to use this information to improve the detection of relevant search results, and compare different strategies for ranking result lists in folksonomy systems.},
  address = {New York, NY, USA},
  author = {Abel, Fabian and Henze, Nicola and Krause, Daniel},
  booktitle = {CIKM '08: Proceeding of the 17th ACM conference on Information and knowledge mining},
  citeulike-article-id = {3500798},
  citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1458082.1458316},
  citeulike-linkout-1 = {http://dx.doi.org/10.1145/1458082.1458316},
  doi = {10.1145/1458082.1458316},
  interhash = {5d6db50409eef97339b135ab8f703538},
  intrahash = {d6d72db224fb84c0b4265f09111483e0},
  isbn = {978-1-59593-991-3},
  location = {Napa Valley, California, USA},
  pages = {1429--1430},
  posted-at = {2009-12-07 00:16:11},
  priority = {2},
  publisher = {ACM},
  title = {Ranking in folksonomy systems: can context help?},
  url = {http://dx.doi.org/10.1145/1458082.1458316},
  year = 2008
}

@inproceedings{abel2009contextbased,
  abstract = {With the advent of Web 2.0 tagging became a popular feature. People tag diverse kinds of content, e.g. products at Amazon, music at Last.fm, images at Flickr, etc. Clicking on a tag enables the users to explore related content. In this paper we investigate how such tag-based queries, initialized by the clicking activity, can be enhanced with automatically produced contextual information so that the search result better fits to the actual aims of the user. We introduce the SocialHITS algorithm and present an experiment where we compare different algorithms for ranking 
users, tags, and resources in a contextualized way.},
  address = {New York, NY, USA},
  author = {Abel, Fabian and Baldoni, Matteo and Baroglio, Cristina and Henze, Nicola and Krause, Daniel and Patti, Viviana},
  booktitle = {HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia},
  interhash = {0e0dff0c21fd77d2d1f0224317c4974f},
  intrahash = {17d5c35426963e20875ec1dc42913855},
  month = {July},
  paperid = {fp060},
  publisher = {ACM},
  session = {Full Paper},
  title = {Context-based Ranking in Folksonomies},
  year = 2009
}